Seismic data is typically used to identify and/or characterize the geologic structures, such as oil and gas reservoirs, underlying the earth's surface. Seismic data is acquired by: (1) generating elastic wave energy at a multiplicity of locations at or near the earth's surface, or within the subsurface; (2) transmitting the generated elastic wave energy into the earth's subsurface where properties associated with the underlying geological structures affect (reflect and/or refract) the transmitted wave energy; and (3) recording the affected, elastic wave energy received at a multiplicity of receiver locations at or near the earth's surface, or within the subsurface. Seismic data processing methods apply a range of digital signal processing algorithms to the recorded data to produce an elastic wavefield image that delineates the effects of the underlying geologic structures upon the wave as the wave propagated through the earth's subsurface. These delineations are then used to draw conclusions about the underlying geological structures.
In many cases, the ability to manage the production of, for example, an oil reservoir is enhanced by an understanding of the ways in which the properties of the underlying geological structures associated with the reservoir have changed over time. For instance, the removal of oil from a location in a reservoir may have, over time, changed the elastic rock properties associated with that location of the reservoir. Knowing that these changes have occurred may be useful in identifying the location at which another well should be placed to realize better production from the reservoir than if the information had not been known.
To facilitate the acquisition of information on changes in the properties associated with subsurface geological structures of a particular volume of the subsurface, a first seismic image of the volume is produced, a second image is then produced at a later time, and the differences between the two images are used to infer changes in the properties of the underlying geological structures. This repeated acquisition of seismic data over time and comparison of the data obtained at different times is commonly referred to as time-lapse or 4-D seismic processing. Some of the rock properties that can change over time and affect elastic wave propagation characteristics include variations in fluid properties, fluid composition, fluid pore pressure, stress conditions and changes in porous rock framework and mineralogy.
The ability to detect these time-lapse changes in the properties of the underlying geologic structure, and to position them in their correct spatial location in the subsurface, is dependent on the magnitude of the changes and the presence of "noise" in the two images. Noise is the portion of the recorded data or signal that cannot be attributed to the properties of interest and, as such, tends to obscure the portion of the data or signal that is of interest. Consequently, the presence of noise can cause erroneous interpretation and inefficient management of, for example, an oil reservoir. A measure of the extent to which noise is obscuring the signal of interest is known as the signal-to-noise ratio. Noise can be in the form of random or semi-random vibrations at the source or receiver locations that is caused by ambient or cultural conditions. A second form of noise is the changes in elastic wave propagation characteristics that occur over time found in the earth's near-surface (the upper 50 to 300 meters). This second class of noise can be similar in appearance to the desired elastic wave signatures associated with monitoring fluids in the subsurface. A third form of noise is elastic wave propagation variations due to shallower reservoir production, or stress changes above or below a reservoir zone of interest.
Presently, there are two digital signal processing methods that are applied to seismic data in an effort to improve the signal-to-noise ratio in 4-D surveys and thereby provide a more accurate image of the changes to the sub-surface geological structures. The first method is the "surface-consistent processing of separate data volumes" method. Characteristic of this method is that the correction, which is accomplished with filters, is independently determined for each of the time lapse images. The usefulness of this method is limited to providing correction for changes in the propagation characteristics that occur over time in the earth's near surface. Corrections due to changes in propagation effects shallower than the reservoir zone in the subsurface are difficult to reconcile with this method. This method is further limited to situations in which there is a high signal-to-noise ratio at the outset. If the signal-to-noise ratio is low, the derivation of the correction filters will be contaminated. A low signal-to-noise ratio can be attributed to (1) a large noise signal relative to the signal relating to the changes of interest; or (2) a small signal relating to the changes of interest relative to the noise signal. A low signal-to-noise ratio in which there is a relatively large noise signal is the norm for seismic data. Further, a low signal-to-noise ratio in which there is a relatively small signal attributable to the changes of interest is becoming increasing important in efficiently managing oil reservoirs and the like. Stated differently, the ability to identify subtle changes, which produce relatively small signals, is becoming of increasing importance in managing oil reservoirs and the like. In sum, this method of processing time lapse seismic data, while useful, is of limited applicability.
The second method for improving the signal-to-noise ratio is the "post-stack or post-migration" method. Characteristic of this method is the production of a correction filter, often derived from cross-correlation of traces representing the same image trace, that is constrained to operate in the volume above the reservoir or modified by a smoothing or averaging function (matched filtering). The constrained or modified filter is then applied to one of the images to produce a corrected image. Local differences between the corrected image and the other image are interpreted to be related to rock property variations due to the reservoir processes of interest. However, the use of this method also has disadvantages. Namely, differences between the two surveys due to the type of noise associated with changes in the propagation characteristics that occur over time in the earth's near surface cannot be correctly reconciled after the stack or migration step that precedes production of the correction filter. Consequently, it is common practice to first apply surface-consistent processing to the data to address this source of noise and then apply the post-stack or post migration process to the data. Thus, further complicating the processing of the data. Further, because the type of noise associated with propagation effects shallower in the subsurface also cannot be correctly reconciled once the stack or migration step has occurred, the post-stack or post-migration method is of limited usefulness with respect to this type of noise. Additionally, this method is of limited use when there is a low signal-to-noise ratio in which there is a small signal relating to the changes of interest relative to the noise signal. Stated differently, the post-stack or post-migration method has limited ability to detect subtle changes. In sum, this method is also of limited applicability.